Temporal resolution adaptation in real-time bitrate estimation from packed sampled traffic

Packet sampling can greatly reduce traffic measurement overhead in high-speed networks. At the same time, this operation introduces estimation errors that have to be carefully handled to ensure a reasonable measurement accuracy. Recently, a frequency-based approach has been proposed to catch the impact of such errors in bitrate estimation of IP flows at various time-scales. In particular, a closed-form expression for the signal-to-noise ratio has been derived as a function of the packet sampling probability, the bin size, and some basic information about the flow (i.e., first and second order moments of the packet size, and long term average packet-rate). In this work, we adopt this model to design a real-time algorithm that properly tunes the temporal resolution of bitrate estimates available at a router, with the goal of assuring a target measurement accuracy. The effectiveness of the proposed approach has been demonstrated by computer simulations, carried out using real packet traces.